Evidence map›Paper›PMID 31931702›Full record

ArticleBMC genomics2020

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: I: feed efficiency and component traits.

Feng Zhang, Yining Wang, Robert Mukiibi, Liuhong Chen, Michael Vinsky, Graham Plastow, John Basarab, Paul Stothard, Changxi Li

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 2 pooled it
10.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 2 syntheses or guidelines pooled it, 130 citations in OpenAlex.

  1. Sequence-based GWAS meta-analyses for beef production traits.Genetics, selection, evolution : GSE · 2023
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  5. Genome-wide association study of mature cow size traits in American Angus cattle.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Feng ZhangLacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, Canada.
Yining WangLacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, Canada.
Robert MukiibiDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Liuhong ChenLacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, Canada.
Michael VinskyLacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, Canada.
Graham PlastowDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
John BasarabAlberta Agriculture and Forestry, Lacombe Research and Development Centre, 6000 C&E Trail, Lacombe, AB, Canada.
Paul StothardDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Changxi LiLacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, Canada. changxi.li@canada.ca.ORCID http://orcid.org/0000-0002-0092-7047
Agriculture and Agri-Food Canada · CAUniversity of Alberta · CAAgriculture Food and Rural Development · CA

Funding

Alberta Livestock and Meat Agency 2014F047R
6 · The paper itself

Abstract

backgroundGenome wide association studies (GWAS) on residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) were conducted in a population of 7573 animals from multiple beef cattle breeds based on 7,853,211 imputed whole genome sequence variants. The GWAS results were used to elucidate genetic architectures of the feed efficiency related traits in beef cattle.

resultsThe DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants followed a scaled inverse chi-squared distribution to a greater extent. With a threshold of P-value < 1.00E-05, 16, 72, 88, and 116 lead DNA variants on multiple chromosomes were significantly associated with RFI, DMI, ADG, and MWT, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on DMI, ADG, and MWT were found on chromosomes 6, 14 and 20. On average, missense, 3'UTR, 5'UTR, and other regulatory region variants exhibited larger allele substitution effects in comparison to other functional classes. Intergenic and intron variants captured smaller proportions of additive genetic variance per DNA variant. Instead 3'UTR and synonymous variants explained a greater amount of genetic variance per DNA variant for all the traits examined while missense, 5'UTR and other regulatory region variants accounted for relatively more additive genetic variance per sequence variant for RFI and ADG, respectively. In total, 25 to 27 enriched cellular and molecular functions were identified with lipid metabolism and carbohydrate metabolism being the most significant for the feed efficiency traits.

conclusionsRFI is controlled by many DNA variants with relatively small effects whereas DMI, ADG, and MWT are influenced by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory region and synonymous functional classes play a more important role per sequence variant in determining variation of the feed efficiency traits. The genetic architecture as revealed by the GWAS of the imputed 7,853,211 DNA variants will improve our understanding on the genetic control of feed efficiency traits in beef cattle.

Indexed as

Genetic Association StudiesGenome ComponentsGenome-Wide Association StudyQuantitative Trait, HeritableQuantitative Trait LociAnimalsCattleEatingGenetic VariationGenomicsPolymorphism, Single NucleotideWhole Genome SequencingBeef cattleFeed efficiencyGenetic architectureGenome wide association studiesImputed whole genome sequence variants

Identifiers

PMID31931702
PMCPMC6956504
OpenAlexW3010437724

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.